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Mechanical Performance Study of Lithium-Ion Battery Module Under Dynamic Impact Test Read chapter Read first chapter

2019 | OriginalPaper | Chapter

BCRLS-EKF-Based Parameter Identification and State-of-Charge Estimation Approach of Lithium-Ion Polymer Battery in Electric Vehicles

Authors : Zhifu Wang, Zhaojian Liu, Zhi Li

Published in: Proceedings of the 19th Asia Pacific Automotive Engineering Conference & SAE-China Congress 2017: Selected Papers

Publisher: Springer Singapore

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Abstract

It is very important for the battery management system (BMS) in electric vehicles to estimate the state of charge (SOC) of lithium-ion battery (LiB) accurately. This paper firstly established the Thevenin battery model, and the parameters of which are determined by off-line identification method. Then, the bias compensation recursive least squares with forgetting factor (BCRLS) method are used to online identify the parameters of the battery, which can effectively reduce the interference of the noise on the estimation results. Finally, the extended Kalman filter (EKF) method is used to estimate the SOC, and the results of online identification can update the parameters of EKF, so as to achieve a higher estimated accuracy. The results indicate that the maximum estimation errors of voltage and SOC are less than 30 mV and 1%, respectively.

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previous chapter A Study on Thermal Runaway of Commercial Lithium-Ion Cells: Influence of SOC, Cell Chemistry and Ageing Status on Safety Performance
next chapter Design of Triaxial Platform Used on Automobile Parts’ Testing
Literature
1.
Finna P, Fitzpatrick C, Connolly D (2012) Demand side management of electric car charging: benefits for consumer and grid. Energy 42:358e63CrossRef
2.
Xiong R, Sun F, Chen Z, He H (2014) A data-driven multi-scale extended Kalman filtering based parameter and state estimation approach of lithium-ion polymer battery in electric vehicles. Appl Energy 113:463e76CrossRef
3.
Hariharan KS, Kumar VS (2013) A nonlinear equivalent circuit model for lithium ion cells. J Power Sources 222:210e7CrossRef
4.
Xiong R, Sun F, Gong X, He H (2013) Adaptive state of charge estimator for lithium ion cells series battery pack in electric vehicles. J Power Sources 242:699e713CrossRef
5.
Zhang C, Sun F, Zhao H et al (2000) Development of management system for electric vehicle battery series. J Beijing Inst Technol 9(1):35–40
6.
Wang JP, Guo JG, Ding L (2009) An adaptive Kalman filtering based state of charge combined estimator for electric vehicle battery pack. Energy Convers Manag 50(12):3182–3386CrossRef
7.
Li C (2007) Study on parameter identification and SOC estimation of Ni/MH battery for EV. Tianjin University, China
8.
Xiong R, Sun F, He H et al (2013) A data-driven adaptive state of charge and power capability joint estimator of lithium-ion polymer battery used in electric vehicles. Energy 63(1):295–308CrossRef
9.
Li Y, Mao Z, Wang Y (2010) BCRLS Identification method for Hammerstein-Wiener model. Int Conf Measur Technol Mechatron Autom, 745–748. IEEE Computer Society
10.
Yang WL, Yu S, Cao WG (2015) Bias compensation recursive least squares identification algorithm for MISO stochastic systems. Info Comput Autom—Int Conf, 659–662
11.
Xiong R, He H, Sun F, Zhao K (2012) Online estimation of peak power capability of lion batteries in electric vehicles by a hardware-in-loop approach. Energies 5(5):1455e69CrossRef
12.
Xiong R, Sun F, Gong X et al (2014) A data-driven based adaptive state of charge estimator of lithium-ion polymer battery used in electric vehicles. Energy 113(1):1421–1433
13.
Xiong R, He H, Sun F, Zhao K (2013) Evaluation on state of charge estimation of batteries with adaptive extended Kalman filter by experiment approach. IEEE Transac Veh Technol 62(1):108e17
14.
Wu G, Zhu C, Chan CC (2010) Comparison of the first order and the second order equivalent circuit model applied in state of charge estimation for battery used in electric vehicles. J Asian Electric Veh 8(1):1357e62
Metadata
Title
BCRLS-EKF-Based Parameter Identification and State-of-Charge Estimation Approach of Lithium-Ion Polymer Battery in Electric Vehicles
Authors
Zhifu Wang
Zhaojian Liu
Zhi Li
Copyright Year
2019
Publisher
Springer Singapore
Book
Proceedings of the 19th Asia Pacific Automotive Engineering Conference & SAE-China Congress 2017: Selected Papers

Print ISBN: 978-981-10-8505-5

Electronic ISBN: 978-981-10-8506-2

Copyright Year: 2019

DOI
https://doi.org/10.1007/978-981-10-8506-2_43

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